Obesity Factors Among Herat Adults

Ghazanfar Medical Journal, Volume 2, Issue 01, March 2017
11

Pattern of Obesity and Associated Factors among Herat
Adult Citizens in Afghanistan

Abstract
Background: Obesity is increasing throughout the world and has become a significant public health
challenge of current century. This study aims to estimate the prevalence of obesity and determine
potential influencing factors among adults in Herat City of Afghanistan.
Methods and Materials: A cross sectional study was conducted using WHO STEP‐wise instrument
among adults aged 25‐70 years during May‐June 2015 in Herat City. Demographic, socioeconomic and
behavioral variables were collected using structured questionnaire. The Body Mass Index (BMI) was
calculated by measuring height and weight. Biochemical markers were examined using blood serums
collected from the field.
Results: Of 1,129 enrolled study participants 47.4% were males, 52.6% were females. Illiteracy rate was
(54%) and 85.8% were married. Prevalence of smoking was 5.6% and 10.8% were mouth snuﬀ users.
Mean Body Mass Index of female and male were 26±6 and 24±4, respectively. Overall, 31.8% were
overweight, of which 35.6% were women and 27.6% men. The overall prevalence of obesity was 15.7%
with diﬀerentiation of 19.3% in females and 11.8% in males. Furthermore, the proportion of obesity
grade one to three in women were 12.2%, 5.2% and 1.9% respectively. This proportion in men were
10.1%, 1.3% and 0.4%. The combined prevalence of both overweight and obesity was 47.6%. The overall
prevalence of central obesity was 52.3% while it was reported 72.1% in females and 30.3% in males. The
biochemical measurements findings show the mean and SD of total triglycerides, cholesterol, HDL, LDL,
and fasting blood sugar were 155.3 ± 61.6, 180.7 ± 47, 45.2 ± 10, 104.5 ± 38.2, and 92.3 ± 86.2 mg/dL,
respectively. The factors such as age, sex, blood pressure, frequency of taking fruits and level of
triglycerides were independently associated with obesity after controlling for other variables.
Conclusions: This study reported high prevalence of obesity among adult residents of Herat City. The
results of this study provide useful information to inform policy makers to prevent and control the
occurrence of obesity.
Keywords: Pattern, Obesity, Overweight, Adults, BMI, Kabul, Afghanistan
Khwaja Mir Islam Saeed, MD, MCs    Head of Grants and Contract Management
Unit (GCMU), Ministry of Public Health, Kabul
Afghanistan,
Cell Phone: 0093 (0) 700290955
Email: kmislamsaeed@gmail.com

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‫اﻓﻐﺎﻧﺴﺘﺎن‬ ‫ات‬‫ﺮ‬‫ﻫ‬ ‫ﺷﻬﺮ‬ ‫در‬ ‫ﺑﺎﻟﻎ‬ ‫اد‬‫ﺮ‬‫اﻓ‬ ‫ﺑﯿﻦ‬ ‫در‬ ‫آن‬ ‫ﺑﻪ‬ ‫ﻣﺮﺗﺒﻂ‬ ‫ﻫﺎی‬ ‫ﻓﮑﺘﻮر‬ ‫و‬ ‫ﭼﺎﻗﯽ‬ ‫ﺳﻄﺢ‬
‫ﭼﮑﯿﺪه‬
‫ﻣﻨﻈﺮ‬ ‫ﭘﺲ‬:‫ا‬‫ﺰ‬‫اﻓ‬ ‫ﺑﻪ‬ ‫رو‬ ‫ﺟﻬﺎن‬ ‫در‬ ‫ﭼﺎﻗﯽ‬ ‫ﺳﻄﺢ‬‫در‬ ‫و‬ ‫ﺑﻮده‬ ‫ﯾﺶ‬‫ﺟﺪﯾﺪ‬ ‫ﭼﺎﻟﺶ‬ ‫ﯾﮏ‬ ‫ﻣﻨﺤﯿﺚ‬ ‫ﺣﺎﴐ‬ ‫ﻗﺮن‬‫د‬‫اﺳﺖ‬ ‫منﻮده‬ ‫اﻧﺪام‬ ‫ﻋﺮض‬ ‫ﻋﺎﻣﻪ‬ ‫ﺻﺤﺖ‬ ‫ﺑﺨﺶ‬ ‫ر‬.
‫اﺳﺖ‬ ‫ﺷﺪه‬ ‫رﯾﺰی‬ ‫ﻃﺮح‬ ‫ات‬‫ﺮ‬‫ﻫ‬ ‫ﺷﻬﺮ‬ ‫ﺑﺎﻟﻎ‬ ‫اد‬‫ﺮ‬‫اﻓ‬ ‫ﺑﯿﻦ‬ ‫در‬ ‫ﭼﺎﻗﯽ‬ ‫روی‬ ‫ﮔﺬار‬ ‫ﺗﺎﺛﯿﺮ‬ ‫ﻫﺎی‬ ‫ﻓﮑﺘﻮر‬ ‫ﺗﻌﯿﻦ‬ ‫و‬ ‫ﺷﯿﻮع‬ ‫ﺗﺨﻤﯿﻦ‬ ‫ﻫﺪف‬ ‫ﺑﻪ‬ ‫ﻣﻄﺎﻟﻌﻪ‬ ‫اﯾﻦ‬.
‫ﻣﯿﺘﻮد‬:‫ﺳﺎزﻣﺎ‬ ‫ﯾﯽ‬ ‫ﻣﺮﺣﻠﻪ‬ ‫روش‬ ‫ﻃﺮﯾﻖ‬ ‫از‬ ‫ﻋﺮﺿﺎﻧﯽ‬ ‫ﺗﺤﻘﯿﻘﯽ‬ ‫ﻣﯿﺘﻮد‬ ‫از‬ ‫اﺳﺘﻔﺎده‬ ‫ﺑﺎ‬‫ﺟﻬﺎن‬ ‫ﺻﺤﯽ‬ ‫ن‬)WHO STEPS Tool(‫ﻣﻮرد‬ ‫در‬ ‫ﻻزم‬ ‫ﻣﻌﻠﻮﻣﺎت‬ ‫و‬
‫ﺑﺎﻟﻎ‬ ‫اد‬‫ﺮ‬‫اﻓ‬۲۵‫اﻟﯽ‬۷۰‫ﻣﯽ‬ ‫ﻣﺎه‬ ‫در‬ ‫ﺳﺎل‬۲۰۱۵‫ﮔﺮدﯾﺪ‬ ‫آوری‬ ‫ﺟﻤﻊ‬ ‫ات‬‫ﺮ‬‫ﻫ‬ ‫ﺷﻬﺮ‬ ‫در‬.‫اﻗﺘﺼﺎدی‬ ،‫اﻓﯿﮏ‬‫ﺮ‬‫دﯾﻤﻮﮔ‬ ‫ارﻗﺎم‬-‫ﺑﺎ‬ ‫ﺳﻠﻮﮐﯽ‬ ‫ﻫﺎی‬ ‫ﻣﺘﺤﻮل‬ ‫و‬ ‫اﺟﺘامﻋﯽ‬
‫ﮔﺮدﯾﺪ‬ ‫آوری‬ ‫ﺟﻤﻊ‬ ‫ﺳﺎﺧﺘﺎری‬ ‫ﭘﺮﺳﺸﻨﺎﻣﻪ‬ ‫از‬ ‫اﺳﺘﻔﺎده‬.‫ﻣ‬ ‫از‬ ‫اﺳﺘﻔﺎده‬ ‫ﺑﺎ‬‫ﺘ‬‫اﻧﺪﮐﺲ‬ ‫ﻗﺪ‬ ‫و‬ ‫وزن‬ ‫ﻫﺎی‬ ‫ﺤﻮل‬‫ﯾﺎ‬ ‫ﻋﻀﻮﯾﺖ‬ ‫ﮐﺘﻠﻮی‬)BMI(‫ﮔﺮدﯾﺪ‬ ‫ﻣﺤﺎﺳﺒﻪ‬.
‫ﮔﺮدﯾﺪ‬ ‫ﺗﻌﯿﻦ‬ ‫اﺗﻮار‬‫ﺮ‬‫ﻻﺑ‬ ‫در‬ ‫ﺧﻮن‬ ‫ﺳﯿﺮوم‬ ‫ﻣﻌﺎﯾﻨﺎت‬ ‫ای‬‫ﺮ‬‫اﺟ‬ ‫ﻃﺮﯾﻖ‬ ‫از‬ ‫ﺑﯿﻮﺷﯿﻤﯽ‬ ‫ﻫﺎی‬ ‫ﺷﺎﺧﺺ‬.
‫ﻧﺘﺎﯾﺞ‬:‫ﻣﻄﺎﻟﻌﻪ‬ ‫اﯾﻦ‬ ‫در‬ ‫ﺷﺎﻣﻞ‬ ‫اد‬‫ﺮ‬‫اﻓ‬ ‫ﺟﻤﻠﻪ‬ ‫از‬)۱۱۲۹(۴۷.۴%‫و‬ ‫ﻣﺮدان‬۵۲.۵%‫ﻣﯿﺪاد‬ ‫ﺗﺸﮑﯿﻞ‬ ‫زﻧﺎن‬ ‫را‬ ‫آﻧﻬﺎ‬.‫ﺑﯿﺴﻮادی‬ ‫ﺳﻄﺢ‬۵۴%‫و‬ ‫ﺑﻮده‬۸۵.۸%
‫ﮔ‬ ‫ﻣﺘﺎﻫﻞ‬‫ﺰ‬‫اﺳﺖ‬ ‫ﺷﺪه‬ ‫ارش‬.‫ﺳﻄﺢ‬‫ﺳﮕﺮت‬ ‫منﻮدن‬ ‫دود‬ ‫ﺷﯿﻮع‬۵.۶%‫در‬ ‫ﺑﻮده‬‫ﺣﺎﻟﯿﮑﻪ‬۱۰.۸%‫ﻣﯿﮑﺮدﻧﺪ‬ ‫اﺳﺘﻔﺎده‬ ‫دﻫﻦ‬ ‫ﻧﺼﻮار‬.‫اﻧﺪﮐﺲ‬ ‫اوﺳﻂ‬ ‫ﺳﻄﺢ‬
‫ﯾﺎ‬ ‫ﺑﺪن‬ ‫ﮐﺘﻠﻮی‬)BMI(‫ﺑﺎﻟﱰﺗﯿﺐ‬ ‫ﻣﺮدﻫﺎ‬ ‫و‬ ‫ﻫﺎ‬ ‫ﺧﺎﻧﻢ‬ ‫در‬26±6‫و‬24±4‫اﺳﺖ‬ ‫ﮔﺮدﯾﺪه‬ ‫ﻣﺤﺎﺳﺒﻪ‬.‫ﻣﺠﻤﻮع‬ ‫در‬۳۵.۵%‫و‬ ‫ﻫﺎ‬ ‫ﺧﺎﻧﻢ‬۲۷.۶%‫اﺿﺎﻓﻪ‬ ‫ﻣﺮدان‬
ُ‫ﮐ‬ ‫ﺳﻄﺢ‬ ‫ﺣﺎﻟﯿﮑﻪ‬ ‫در‬ ‫ﺑﻮدﻧﺪ‬ ‫وزن‬‫وزﻧﯽ‬ ‫اﺿﺎﻓﻪ‬ ‫ﻠﯽ‬۳۱.۸%‫ﺑﻮد‬.‫ﭼﺎﻗﯽ‬ ‫ﻋﻤﻮﻣﯽ‬ ‫ﺳﻄﺢ‬۱۵.۷%‫ﺗﻔﺎوت‬ ‫ﮐﻪ‬ ‫ﺑﻮده‬۱۹.۳%‫و‬ ‫ﻫﺎ‬ ‫ﺧﺎﻧﻢ‬ ‫در‬۱۱.۸%‫در‬ ‫ا‬‫ر‬
‫ﻣﯿﺪﻫﺪ‬ ‫ﻧﺸﺎن‬ ‫ﻣﺮدﻫﺎ‬.‫اول‬ ‫درﺟﻪ‬ ‫ﭼﺎﻗﯽ‬ ‫ﺳﻄﺢ‬ ،‫اﯾﻨﻬﺎ‬ ‫ﺑﺮ‬ ‫ﻋﻼوه‬۱۲.۲%‫دوم‬ ‫درﺟﻪ‬ ‫ﭼﺎﻗﯽ‬ ،۵.۲%‫ﺳﻮم‬ ‫درﺟﻪ‬ ‫ﭼﺎﻗﯽ‬ ‫و‬۱.۹%‫ﮔ‬ ‫ﻫﺎ‬ ‫ﺧﺎﻧﻢ‬ ‫ﻧﺰد‬‫ﺰ‬‫داده‬ ‫ارش‬
‫اﺳﺖ‬ ‫ﺷﺪه‬.‫در‬‫اول‬ ‫درﺟﺎت‬ ‫در‬ ‫ﻣﺮدان‬ ‫ﭼﺎﻗﯽ‬ ‫ﺳﻄﺢ‬ ‫ﺣﺎﻟﯿﮑﻪ‬،‫ﺑﺎﻟﱰ‬ ‫ﺳﻮم‬ ‫و‬ ‫دوم‬‫ﺗﯿﺐ‬۱۰.۱%،۱.۳%‫و‬ ،۰.۴%‫اﺳﺖ‬ ‫ﺷﺪه‬ ‫ﻣﺤﺎﺳﺒﻪ‬.‫ﺗﺮﮐﯿﺒﯽ‬ ‫ﺑﺼﻮرت‬
‫وزﻧﯽ‬ ‫اﺿﺎﻓﻪ‬ ‫و‬ ‫ﭼﺎﻗﯽ‬ ‫ﻣﺸﱰک‬ ‫ﺳﻄﺢ‬۴۷.۶%‫ﻣﯿﺒﺎﺷﺪ‬.‫اوﺳﻂ‬ ‫ﺑﮕﻮﻧﻪ‬‫ﻣﺮﮐﺰی‬ ‫ﭼﺎﻗﯽ‬ ‫ﻋﻤﻮﻣﯽ‬ ‫ﺳﻄﺢ‬۵۲.۳%‫ﺑﻮده‬‫در‬ ‫رﻗﻢ‬ ‫اﯾﻦ‬ ‫ﮐﻪ‬‫زﻧﺎن‬۷۲.۱%‫در‬ ‫و‬
‫ﻣﺮدان‬۳۰.۳%‫ﺷﺪ‬ ‫داده‬ ‫ﻧﺸﺎن‬.‫ﻣﻌ‬ ‫اف‬‫ﺮ‬‫اﻧﺤ‬ ‫و‬ ‫اوﺳﻂ‬ ‫ﮐﻪ‬ ‫ﻣﯿﺪﻫﺪ‬ ‫ﻧﺸﺎن‬ ‫ﺑﯿﻮﺷﯿﻤﯿﮏ‬ ‫ﻫﺎی‬ ‫درﯾﺎﻓﺖ‬ ‫ﮔﯿﺮی‬ ‫اﻧﺪازه‬‫ا‬‫ﺮ‬‫ﺗ‬ ‫ﻣﻘﺎدﯾﺮ‬ ‫ﯿﺎری‬‫ی‬،‫ﻣﺠﻤﻮﻋﯽ‬ ‫اﯾﺪ‬‫ﴪ‬‫ﮔﻠﯿ‬
‫ﺑﺎﻟﱰﺗﯿﺐ‬ ‫ﮔﺮﺳﻨﮕﯽ‬ ‫ﻣﺮﺣﻠﻪ‬ ‫در‬ ‫ﮔﻠﻮﻟﻮز‬ ‫ﺳﻄﺢ‬ ‫و‬ ‫ﭘﺎﯾﯿﻦ‬ ‫اﮐﻢ‬‫ﱰ‬‫ﻣ‬ ‫ﻟﯿﭙﻮﭘﺮوﺗﯿﻦ‬ ،‫ﺑﻠﻨﺪ‬ ‫اﮐﻢ‬‫ﱰ‬‫ﻣ‬ ‫ﻟﯿﭙﻮﭘﺮوﺗﯿﻦ‬ ،‫ﮐﻮﻟﺴﱰول‬155.3 ± 61.6،۱۸۰.۷±۴۷،۴۵.۲±
۱۰،104.5 ± 38.2،٩٢.٣±٨٦.٢‫اﺳﺖ‬ ‫ﺑﻮده‬ ‫ﻟﯿﱰ‬ ‫دﯾﺴﯽ‬ ‫ﻓﯽ‬ ‫ام‬‫ﺮ‬‫ﻣﻠﯿﮕ‬.‫ﺧ‬ ‫ﻓﺸﺎر‬ ،‫ﺟﻨﺴﯿﺖ‬ ،‫ﺳﻦ‬ ‫ﻣﺜﻞ‬ ‫ﻫﺎی‬ ‫ﻓﮑﺘﻮر‬‫ﺳﻄﺢ‬ ‫و‬ ‫ﻣﯿﻮه‬ ‫اﺧﺬ‬ ‫ﻓﺮﯾﮑﻮﻧﺴﯽ‬ ،‫ﻮن‬
‫ا‬‫ﺮ‬‫ﺗ‬‫ی‬‫اﺳﺖ‬ ‫داﺷﺘﻪ‬ ‫ارﺗﺒﺎط‬ ‫ﭼﺎﻗﯽ‬ ‫ﺑﺎ‬ ‫ﻫﺎ‬ ‫ﻣﺘﺤﻮل‬ ‫ﺳﺎﯾﺮ‬ ‫ﮐﻨﱰول‬ ‫از‬ ‫ﺑﻌﺪ‬ ‫ﻣﺴﺘﻘﻼﻧﻪ‬ ‫و‬ ‫ﻣﺸﺨﺺ‬ ‫ﺑﺼﻮرت‬ ‫اﯾﺪ‬‫ﴪ‬‫ﮔﻠﯿ‬.
‫ﮔﯿﺮی‬ ‫ﻧﺘﯿﺠﻪ‬:‫ﻣﯿﺪﻫﺪ‬ ‫ﻧﺸﺎن‬ ‫ات‬‫ﺮ‬‫ﻫ‬ ‫ﺷﻬﺮ‬ ‫در‬ ‫ﺷﻬﺮی‬ ‫ﺑﺎﻟﻎ‬ ‫ﺳﺎﮐﻨﯿﻦ‬ ‫ﺑﯿﻦ‬ ‫در‬ ‫را‬ ‫ﭼﺎﻗﯽ‬ ‫ﺷﯿﻮع‬ ‫ﺑﻠﻨﺪ‬ ‫ﺳﻄﺢ‬ ‫ﻣﻄﺎﻟﻌﻪ‬ ‫اﯾﻦ‬.‫ﻣﻌﻠﻮﻣﺎت‬ ‫ﺗﺤﻘﯿﻖ‬ ‫اﯾﻦ‬ ‫ﻧﺘﺎﯾﺞ‬
‫ﺑ‬ ‫را‬ ‫ﻣﻔﯿﺪی‬‫ﻣﻨﻈﻮر‬ ‫ﻪ‬‫آ‬‫ﮔﺎ‬‫ﻣﯿﻨامﯾﺪ‬ ‫ﻣﻬﯿﺎ‬ ‫ﭼﺎﻗﯽ‬ ‫وﻗﻮع‬ ‫ﮐﻨﱰول‬ ‫و‬ ‫ﺟﻠﻮﮔﯿﺮی‬ ‫ﺑﺨﺎﻃﺮ‬ ‫ان‬‫ز‬‫ﺳﺎ‬ ‫ﭘﺎﻟﯿﺴﯽ‬ ‫ﻫﯽ‬.

Introduction
Obesity is increasing throughout the world and
has become a significant public health challenge
of current century (1‐3). Globally, it is estimated
that more than 2 billion people are overweight
and one third of them are obese (4). Obesity is
considered a chronic disease due to enduring
imbalance between energy intake and output. It
is a multifactorial disease influenced by
socioeconomic, cultural, environmental, and
public policy factors (5). Regretfully it is
culminated to a wide range of serious health
consequences, such as diabetes, hypertension,
cardiovascular disease, and some forms of
cancer (6). Nowadays taking fast food is
common which is considered to be an
important cause of increased obesity risk (7‐8).
Furthermore, factors such as age, gender,
urbanization, education status, economic
status, marriage, physical activity, smoking, and
alcohol consumption and diet are contributing
to obesity (9‐11). Obesity is measured by
various methods such as body mass index
(BMI), waist circumference, waist‐hip ratio,

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skinfold, and percent body fat measurements
(12).
In Eastern Mediterranean Region (EMR)
countries, obesity has reached to its alarming
level in all age groups. Among adults the
prevalence of overweight and obesity ranged
from 25% to 81.9%. Possible factors
determining obesity in this region include:
nutrition transition, inactivity, urbanization,
marital status, a shorter duration of
breastfeeding, frequent snacking, skipping
breakfast, a high intake of sugary beverages, an
increase in the incidence of eating outside the
home, long periods of time spent viewing
television, massive marketing promotion of high
fat foods, stunting, perceived body image,
cultural elements and food subsidization policy
(13). In Pakistan, as eastern neighbour of
Afghanistan, with the use of Indo‐Asian specific
BMI cut off values, the prevalence of
overweight and obesity has been reported to be
25% and 10.3%, respectively. The factors
independently and significantly associated with
overweight and obesity include greater age,
being female, urban residence, being literate,
economic status and intake of meat (14). In
Iranian adult population, the prevalence of
overweight, obesity and pathologic obesity is
reported to be 40%, 35% and 3%, respectively
with significant difference by age, gender,
education level, economic status, and residence
(15). Recent studies in Kabul (16) show that
prevalence of obesity in age group of ≥40 years
is 31.2% and in Jalalabad City (17), the eastern
city of the country, is 27.4%. Previous studies in
Kabul and Nangarhar focused only on provincial
regions of the country while the new study
provides information from a different context.
However, due to war and conflict very few
information is available on burden of non‐
communicable diseases including obesity. In
addition, high priority is given to infectious
diseases. This study aims to identify the
prevalence and associated factors of obesity in
Herat City.
Methods and materials
A provincial cross‐sectional study during May‐
June 2015 using the WHO STEP‐wise approach
(18) was conducted to estimate the prevalence
and factors for non‐communicable diseases in
Herat City, Afghanistan. While this study reports
the burden of obesity and factors associated
with diseases among urban adult citizens
utilizing data from the main study.
Sampling Size and Strategy: As data
regarding risk factor prevalence in this province
were not available, we assumed the highest
prevalence and 95% conﬁdence interval and
band of error of 5%. Basically, the sample size
was calculated to be able to determine the
effect of risk factors on non‐communicable
diseases. The resulting sample size was 1,200.
Multi‐cluster sampling strategy was used to
identify the final unit, households, to be
approached for interview, filling questionnaire.
For this reason, the 2015 Expanded Programme
for Immunization (EPI) list of clusters was used
as the sampling frame. Using multi‐stage cluster
sampling, in the first stage we conventionally
and randomly selected 16 out of 60 EPI clusters.
In the second stage, from each selected clusters
five areas (Guzar) were randomly selected.
1200 households were selected using
population proportionate to size of households
in each cluster/ area. Our primary sampling unit
(PSU) was clusters, secondary sampling units
(SSU) were streets/areas, tertiary sampling
units (TSU) were households, and ultimate
sampling units (USU) were respondents more
25‐70 years of age in the household. Inclusion
criteria included: ages 25‐70, city residents
during study period, and consent to participate.
Exclusion criteria included: temporary residents

14
(less than six months) and those living in
institutionalized settings such as universities,
prisons, barracks or in insecure areas, not
consent to participate. The interviewer was
instructed to find the masjid as a fixed landmark
or a very populated street within the
boundaries of the selected location and,
following the bottle rotating rule, proceed to
series of households. The survey team consisted
of male and female to observe the cultural
sensitivity of society.
Variables and Data Collection Tool: Data
collection tool (WHO STEPS) adapted in advance
used to collect demographic, socio‐economic,
clinical, and behavioral data via face‐to‐face
interviews. Weighing scales and tension tape
were used to measure body weight and height.
A body mass index (BMI hereafter reported
without units) ≥ 30 kg/m2
was considered as
obese, 25‐29.9 was considered as overweight,
and 18.5‐24.9 was considered normal weight
(19). Likewise, the obesity grades I, II and III
were categorized in BMI scale as 30‐35, 35‐40
and >40, respectively. A waist circumference
≥94 cm for men and ≥80 cm for women was
considered as central obesity (20). Cuﬀ type
sphygmomanometers were used to measure
systolic and diastolic blood pressure (BP) thrice
with five minutes between each measurement
at a sitting or lying position by trained
surveyors. Systolic blood pressure levels ≥140
mmHg and/or diastolic pressure levels ≥90
mmHg were considered hypertensive (21).
Hypertension (HTN) in this study was defined as
having a previous diagnosis of disease or being
diagnosed by measurement during the study.
Blood samples were collected and processed by
lab technicians under supervision of the lab
coordinator. After shipment of samples to the
Central Public Health Laboratory (CPHL) in
Kabul, they were stored at ‐80°C until glucose
and biochemical measurements were
completed. For enhancing quality of data close
monitoring was carried out throughout the
processes. Epi Info version 7 (22) was used for
data entry. IBM SPSS software version 20 (23)
was used for data analysis. Chi‐square and
logistic regression was used to examine the
association of relevant variables at univariate
and multivariate levels. For this study a blanket
approval was obtained for main survey by the
institutional review board (IRB) of the Ministry
of Public Health. Written informed consent was
taken from each individual before the interview
while it was read for illiterates. The results of
physical and biochemical measurements were
communicated to participants while
confidentiality of the information gathered was
maintained. Biochemical tests were done by
central public health laboratory using their own
kits. Cut off point for total tri‐glyceride, total
cholesterol, high density lipoprotein (HDL) and
low density lipoprotein (LDL) was considered as
150, 190, 40 (50 for female) and 100mg/dL,
respectively.
Results
Descriptive Analysis: After validation and
cleaning, 1,129 (94%) out of 1,200 participants
were eligible (having blood specimen) for
analysis including men and women aged 25‐70
years. The analysis was done on 1,125 records
which had full information of BMI calculations,
whereas four records excluded due to lacking
complete BMI information. For few variables
there are missing data which is reported in
tables.
Out of these, 47.4% were males and 52.6%
females. Mean age of this sample was 41.5
±13.1 years. More than half of the respondents
(54%) were illiterates, and 82.7% of participants
had a monthly income <10,000 Afghanis
(equivalent to approx. USD 150). Majority of the
study participants were married (85.8%), while

15
more than 80% of women were housewives
(table 1). Mean height, waist circumference and
weight were 162, 87cm, and 66.6kg
respectively. Mean and standard deviation (SD)
of body mass index was 25.4 ± 5.3 kg/m2
.
Descriptive statistics demonstrated that 5.6%
were current smokers of which half had smoked
for 10 years or more while about twice of that
(10.8%) were mouth snuff users. Around 45% of
respondents reported to use liquid oil for
cooking. On average, the subjects were taking
fruits 2.14 days per week and vegetables 2.89
days per week. Ten percent of respondents
were employed at jobs that required vigorous
physical activity and 21.6% at moderate levels
of physical activity.
The overall prevalence of overweight was 31.8%
while it was found to be 35.6% in women and
27.6% in men. Average Body Mass Index (BMI)
and Standard Deviation (SD) were 26±6 in
women and 24.7±4.3 in men. Moreover, obesity
grade one to three in women were 12.2%, 5.2%,
1.9% and in men 10.1%, 1.3% and 0.4%. In
short, the general prevalence of obesity was
15.7% with differentiation of 19.3% in females
and 11.8% in males. The combined prevalence
of both overweight and obesity was 47.6%. The
biochemical measurements findings show that
mean and SD total triglycerides, cholesterol,
HDL, LDL, and fasting blood sugar were 155.3 ±
61.6, 180.7 ± 47, 45.2 ± 10, 104.5 ± 38.2, and
92.3 ± 86.2 mg/dL, respectively. In general, the
central obesity was 52.3% among participants,
from which 72.1% in females and 30.3% in
males were reported. Almost one third (28.4%)
had higher cholesterol and 45% had higher
triglycerides. Moreover, high LDL level was
47.2% and high HDL level was 47% in both
groups. The full description of these variables
could be reviewed in table 2.
Inferential Analysis: Tables 3 and 4 show the
association of main demographic and
behavioral risk factors with obesity. As shown in
table 3, odds of being obese are increasing as
the age increased. Males were 0.56 times less
obese compared to females (95%CI: 0.40‐0.78).
Although few reported the monthly income
when questioned, available data shows that
level of income as a proxy for socioeconomic
status is associated with obesity (OR=2.33, 95%
CI: 1.40‐3.85). Categorization of taking fruits in
days per week had significant positive
relationship with obesity. Those who were
taking fruits three or more days per week had
odds of 1.68 as compared to those taking fruits
less than three days per week (95% CI: 1.24‐
2.51). This is a surprising finding which shows
taking fruits have led to obesity. It requires
further investigations and analysis. We could
not find any significant association of education
level, marital status, physical activity and
smoking with obesity. Central obesity using
waist circumference was also associated with
general obesity using level of BMI (OR=15.45,
95%CI: 8.66‐27.58). Moreover, those who were
hypertensive had 2.64 times (95% CI: 1.90‐3.65)
more odds of being obese. Level of blood bio‐
chemicals such as triglycerides, total
cholesterol, HDL, LDL and fasting blood sugar
were not significantly associated with obesity at
bivariate level.
After running multiple logistic regressions,
factors such as age, sex, blood pressure,
frequency of taking fruits and level of
triglycerides were independently associated
with obesity after controlling for other
variables. Table 5 shows further details.
Discussion
Based on findings almost 16% of adult citizens
were found to be obese and by adding the
overweight it raised to 47.5%. This percentage

16
increased as age increased in females. Although
this percentage is very low as compared to
other studies in Afghanistan and other
countries, nonetheless overweight and obesity
should be considered as a significant public
health problem in urban population particularly
among females in Herat City. Most of the
studies have reported higher prevalence of
overweight and obesity among women than
men and that may be due to lower physical
activity among women (16‐17, 24‐28). As
mentioned earlier, higher age was associated
with higher proportion of obesity. It could be
due to lower physical activity and impact of
hormonal changes by increasing age. The
association of age and obesity has been studied
by other studies (16‐17, 29‐30). Foods, for
instance fruits and red meat were associated to
obesity. Taking fruits as a meal could prevent
gaining weight and it is mostly due to its
content. Nonetheless consumption of red and
fatty meat during lunch and dinner in various
forms are common which has been associated
with obesity in this study; however, the results
are not significant. Many studies have reflected
the association of food stuﬀ and obesity (17,
31‐32). Blood pressure combined with obesity
has been reported in our study which is
significantly associated to each other. These
findings have been reported by other studies in
Afghanistan (16, 17) as well as in other
countries (14, 33). Level of triglyceride was
associated with obesity which has been
reported by another study in Jalalabad City as
well (16).
The study has some limitations. First, the results
cannot be generalized to all provinces in
Afghanistan as the study group was from one
urban setting and cannot be assumed to be
representative of all adult populations in the
province. Second, it was a cross sectional study,
therefore, causality of the relationship between
the factors reported and obesity is not possible
to be ascertained. Third, we excluded the
insecure areas from our study and because of
fund limitation did not list all households ahead
of survey. Fourth, since this was a study
originally designed for NCD therefore could
inadequately include full risk factors associated
with obesity. However, the finding of this study
is noteworthy because of being first of its kind
in this city as well as sufficient sample size and a
high response rate.
Conclusion
The interventions for control and prevention of
obesity would contribute to avoiding most of
other problems instigating from lifestyle
changes. Designing interventions focusing on
mentioned factors by involvement of other
sectors could reduce the level of obesity in this
city.
Acknowledgement
The original survey was supported by World
Health Organization Office in Kabul as well as by
Afghanistan National Public Health Institute in
the Ministry of Public Health, thus the author
would like to thank these two institutions for
their support. All technical supervisors, data
collectors, study participants for their
contribution in this study are fully thanked.
Conflict of interest
The authors declare there is no conflict of
interest in this paper.

17
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19
Table 1: Frequency distribution of demographic characteristics of the study participants
Variables Categories Subjects (1129)
      Number Percentage
Age
   25‐34 399 35.3
   35‐44 288 25.5
   45‐54 220 19.5
   55+ 222 19.7
Gender
   Female 594 52.6
   Male 535 47.4
Level of Education
   Illiterate 607 54
   Primary and unofficial 380 33.8
   Secondary school 73 6.5
   High school and over 64 5.7
Work Status
   Official Employees 100 10.2
   Private Business 89 9.1
   Worker/Farmer 184 18.8
   Jobless 51 5.2
   Housework 461 47.1
Monthly Income in AFN
   Less than 10000 454 82.7
   More than 10000 95 17.3
Marital Status
   Single 53 4.7
   Married 964 85.8
   Widow/Widower 83 7.4

20

Table 2: Frequency distribution of behavioral risk factors for obesity, among the study
participants
Variables Categories Subjects (1129)
      Number Percentage
Total Cholesterol
   <190 mg/dL 808 71.6
   ≥ 190 mg/dL 321 28.4
LDL
   <100 mg/dL 596 52.8
   ≥100 mg/dL 533 47.2
HDL( borderline 40 mg/dL for male and 50mg/dL for female)
   <40 and 50mg/dL 598 53
   ≥40 and 50mg/dL 531 47
Triglycerides
   <150 mg/dL 621 55
   ≥150 mg/dL 508 45
Fruit serving ( days per week)
   ≤ 3 870 83
   > 3 178 17
Vegetables serving (days per week)
   ≤ 3 762 71.4
   > 3 305 28.6
Type of Kitchen Oil
   Liquid 503 45.2
   Solid 380 34.1
   Both 221 19.8
Cigarette Smoking Status
   No 1055 94.4
   Yes 63 5.6
Mouth Snuff Status
   No 994 89.2
   Yes 120 10.8
Vigorous Physical Activity

21
   No 1004 89.6
   Yes 116 10.4
Moderate Physical Activity
   No 877 78.4
   Yes 241 21.6
Pedal or bicycle for 10 Minutes per day
   No 765 68.4
   Yes 354 31.6
Reclining/siting (hours per day)
   ≤ 3 409 38.9
   > 3 642 61.1

Table 3: Bivariate analysis of bio demographic and socio‐economic factors and Obesity among study
participants in Herat Afghanistan
Variables Categories Non‐obese Obese Odds Ratio CI 95% LL CI 95% UL
Age in years
   25 ‐ 35 354 (89.4) 42 (10.6) 1 Reference
   35 ‐ 45 234 (81.2) 54 (18.8) 1.945 1.258 3.007
   45 ‐ 55 175 (75.9) 45 (20.5) 2.167 1.371 3.426
   55 and over 185 (83.7) 36 (16.3) 1.64 1.016 2.649
Gender
   Female 478 (80.7) 114 (19.3) 1 Reference
   Male 470 (88.2) 63 (11.8) 0.562 0.403 0.784
Level of income (monthly income in AFN)
   < 10,000 382 (84.1) 72 (15.9) 1 Reference
   ≥ 10,000 66 (69.5) 29 (30.5) 2.331 1.408 3.859
Level of education
   Illiterate 502 (83.1) 102 (16.9) 1 Reference
   Literate 441 (85.5) 75 (14.5) 0.837 0.605 1.158
Smoking
   No 883 (84) 168 (16) 1 Reference
   Yes 56 (88.9) 7 (11.1) 0.657 0.294 1.466

22
Snuffing
   No 832 (84) 159 (16) 1 Reference
   Yes 104 (86.7) 16 (13.3) 0.805 0.463 1.4
Strong Physical Activity
   No 840 (83.9) 161 (16.1) 1 Reference
   Yes 101 (87.1) 15 (12.9) 0.775 0.439 1.367
Moderate Physical Activity
   No 740 (84.6) 135 (15.4) 1 Reference
   Yes 199 (82.9) 41 (17.1) 1.129 0.77 1.656
Sedentary lifestyle in hours daily
   ≤ 3 hours 354 (87) 52 (13) 1 Reference
   > 3 hours 531 (83) 111 (17) 1.423 0.997 2.031
Fruits serving days per week
   ≤ 3 days 743 (85.7) 124 (14.3) 1 Reference
   > 3 days 139 (78.1) 39 (21.9) 1.681 1.124 2.515
Vegetables serving days per week
   ≤ 3 days 647 (85.1) 113 (14.9) 1 Reference
   > 3 days 250 (82.2) 54 (17.8) 1.237 0.867 1.765

Table 4: Bivariate analysis of pathophysiologic factors and obesity among study participants in Herat
city Afghanistan
Questions Categorization Non‐obese Obese Odds Ratio CI 95% LL CI 95% UL
Central Obesity
   No 522 (97.6) 13 (2.4) 1 Reference
   Yes 426 (72.2) 164 (27.8) 15.458 8.663 27.583
Diabetes Mellitus
   No 858 (84.6) 156 (15.4) 1 Reference
   Yes 90 (81.1) 21 (18.9) 1.283 0.775 2.126
Blood Pressure
   No 645 (89.1) 79 (10.9) 1 Reference
   Yes 303 (75.6) 98 (24.4) 2.641 1.906 3.659
Total Cholesterol
   <190 mg/dL 675 (83.9) 130 (16.1) 1 Reference
   ≥ 190 mg/dL 273 (85.3) 47 (14.7) 0.894 0.622 1.284

23
Low Density Lipoprotein (LDL)
   <100 mg/dL 499 (84.3) 93 (15.7) 1 Reference
   ≥100 mg/dL 449 (84.2) 84 (15.8) 1.004 0.728 1.384
High Density Lipoprotein (HDL)
   <40 and 50mg/dL 501 (83.9) 96 (16.1) 1 Reference
   ≥40 and 50mg/dL 447 (84.7) 81 (15.3) 0.946 0.685 1.305
Triglycerides
   <150 mg/dL 532 (86.1) 86 (13.9) 1 Reference
   ≥150 mg/dL 416 (82.1) 91 (17.9) 1.353 0.981 1.866
Taking Table Salt
   No 708 (83.2) 143 (16.8) 1 Reference
   Yes 211 (88.3) 28 (11.7) 0.657 0.426 1.013
Taking type of oil kitchen
   Liquid 446 (84.8) 80 (15.2) 1 Reference
   Solid 310 (81.8) 69 (18.2) 1.241 0.872 1.766

24

Table 5: Multivariable analysis of risk factors and obesity among study participants in Herat city
Afghanistan
Questions Categorization Adjusted Odds Ratio CI 95% LL CI 95% UL P Value
Age groups
   25‐35 1 Reference
   35‐45 1.681 1.023 2.764 0.041
   45‐55 1.845 1.095 3.11 0.021
   55 and over 1.129 0.632 2.017 0.682
Sex
   Male 1 Reference
   Female 1.884 1.281 2.769 < 001
Triglycerides

More
1 Reference

Less
1.003 1 1.005 0.035
Average Systolic Blood Pressure
   No 1 Reference
   Yes 1.025 1.015 1.036 0.000
Fruits taking in days per week
   More    Reference
   Less 1.108 1.007 1.218 0.035
Red meat in days per week

More
1 Reference

Less
1.191 1.04 1.364 0.012

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